Identification of Patients with CKD in Medical Databases: A Comparison of Different Algorithms.
2021
BACKGROUND AND OBJECTIVES Despite CKD consensus definitions, epidemiologic studies use multiple different algorithms to identify CKD. We aimed to elucidate if this affects the patient characteristics and the estimated prevalence and prognosis of CKD by applying six different algorithms to identify CKD in population-based medical databases and compare the cohorts. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Patients with CKD in Northern Denmark (2009-2016) were identified using six different algorithms: five were laboratory based defined by (1) one measured outpatient eGFR 60 ml/min per 1.73 m2 observed in-between (Kidney Disease Improving Global Outcomes, persistent, n=68,994), (4) two such findings ≥90 and 30 mg/g ≥90 days apart (Kidney Disease Improving Global Outcomes, eGFR/albuminuria, n=100,957). The sixth included patients identified by reported in- and outpatient hospital International Classification of Diseases diagnoses of CKD (hospital-diagnosed, n=27,947). For each cohort, we estimated baseline eGFR, CKD prevalence, and 1-year mortality using the Kaplan-Meier method. RESULTS The five different laboratory-based algorithms resulted in large differences in the estimated prevalence of CKD from 4637-8327 per 100,000 population. In contrast, 1-year mortality varied only slightly (7%-9%). Baseline eGFR levels at diagnosis were comparable (53-56 ml/min per 1.73 m2), whereas median time since first recorded eGFR <60 ml/min per 1.73 m2 varied from 0 months (single-test) to 17 months (Kidney Disease Improving Global Outcomes, persistent). The hospital-diagnosed algorithm yielded markedly lower CKD prevalence (775 per 100,000 population), a lower baseline eGFR (47 ml/min per 1.73 m2), longer time since first eGFR <60 ml/min per 1.73 m2 (median 70 months), and much higher 1-year mortality (22%). CONCLUSIONS Population prevalence of CKD identified in medical databases greatly depends on the applied algorithm to define CKD. Despite these differences, laboratory-based algorithms produce cohorts with similar prognosis. PODCAST This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_03_11_CJN15691020_final.mp3.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
29
References
3
Citations
NaN
KQI